Feat: Desacoplamento

code/utils/config.py

@@ -0,0 +1,12 @@
+import os
+
+# AWS
+AWS_REGION = os.environ.get("AWS_REGION", "us-east-2")
+BEDROCK_MODEL_ARN = os.environ["BEDROCK_MODEL_ARN"]
+
+# S3
+OUTPUT_BUCKET = os.environ.get("OUTPUT_BUCKET", "upflux-doc-analyzer")
+API_VERSION = os.environ.get("API_VERSION", "v1")
+
+# Langfuse
+LANGFUSE_HOST = os.environ.get("LANGFUSE_HOST", "https://cloud.langfuse.com")

code/utils/langgraph_agent.py

@@ -17,15 +17,16 @@ from langchain_core.messages import HumanMessage, AIMessage, ToolMessage, System
 from langchain_core.tools import tool
 import os
 from langfuse import Langfuse
-from langfuse.langchain import CallbackHandler 
+from langfuse.langchain import CallbackHandler
 from utils.secrets_manager import SECRETS
+from utils.config import AWS_REGION, BEDROCK_MODEL_ARN, LANGFUSE_HOST
 
 CODE=""
 
 langfuse = Langfuse(
     secret_key=SECRETS["LANGFUSE-SECRET-KEY"],
     public_key=SECRETS["LANGFUSE-PUBLIC-KEY"],
-    host=os.environ.get("LANGFUSE_HOST", ""),
+    host=LANGFUSE_HOST,
 )
 
 
@@ -436,14 +437,14 @@ class AgentState(TypedDict):
 
 def get_bedrock_client():
     """Initialize and return AWS Bedrock runtime client."""
-    return boto3.client("bedrock-runtime", region_name="us-east-2")
+    return boto3.client("bedrock-runtime", region_name=AWS_REGION)
 
 
 def create_llm():
     """Create and return the Bedrock LLM."""
     return ChatBedrock(
-        model_id="arn:aws:bedrock:us-east-2:232048051668:application-inference-profile/uy4xskop19zn",
-        region_name="us-east-2",
+        model_id=BEDROCK_MODEL_ARN,
+        region_name=AWS_REGION,
         provider="anthropic"
     )